Abstract 3475: An 18-gene expression model predicts resistance to standard of care therapy on 3-month follow up 18FDG-PET in locally advanced cervical cancer
Authors: Michael R. Waters, Matthew Inkman, Perry W. Grigsby, Stephanie Markovina, Julie K. Schwarz, Jin Zhang
Journal: Cancer Research (2022)

Abstract Introduction: As many as 30-50% of patients with locally advanced cervical cancer (LACC) experience recurrence after chemoradiation therapy (CRT), and five-year survival rates for these patients is only ~10%. While local recurrence and overall survival are useful metrics for analyzing genomic risk factors in LACC, such time to event analysis can be complicated by confounding variables which impede the elucidation of biologically relevant signals. Our group previously reported upregulation of genes from the PI3K pathway in cervical tumors with residual abnormal 18F-Fluoro-deoxy-glucose (FDG) uptake on positron emission tomography (PET) performed 3 months after CRT. Here, we analyzed whole transcriptome data using RNASeq from N=86 prospectively collected pretreatment cervix tumor biopsies to identify novel gene expression signatures associated with persistent or new FDG uptake on 3 month post-therapy FDG-PET. Objective: To identify and validate a predictive gene expression signature able to distinguish primary tumors likely to be resistant to standard of care CRT as assessed by PET scan obtained 3-months following completion of therapy. Methods: Whole tumor RNA-seq analysis was performed on 86 pre-treatment tumor specimens and compared with associated 3-month post-CRT FDG-PET. Response was dichotomized into metabolic complete response (mCR) and persistent/new disease (mP/N) defined as persistent or new areas of FDG-uptake on post-CRT PET per the nuclear medicine report. Differential expression analysis was conducted using the EdgeR R-package. Pathway enrichment analysis was conducted using reference libraries as specified and EnrichR software. Decision tree modeling, hyperparameter optimization, and k-fold cross-validation was performed using the sci-kitlearn python package. Results: We identified an 18-gene expression signature predictive for mCR vs. mP/N in patients treated with definitive CRT with an overall prospective accuracy of 0.92. This model reliably identified both classes of patients (mCR F1=0.95, precision = 0.90, recall =1.0 ; mP/N F1=0.80, precision 0.67, recall =1.0). Crowd source enrichment analysis using EnrichR identified an NRF2 driven expression program (p=0.0006), and an altered inflammatory response (0.000006) within the predictive 18 gene signature. Conclusions: We generated an 18-gene model to predict response to CRT as assessed by 3 month PET imaging. This novel expression signature further identified the NRF2 transcription factor as an important marker for resistance to CRT, consistent with previous studies showing NRF2 promotes cervical cancer growth. Our findings highlight the need for further elucidation of the NRF2 pathway in LACC, and can be used to accurately assess high risk patients who would benefit from treatment escalation. Citation Format: Michael R. Waters, Matthew Inkman, Perry W. Grigsby, Stephanie Markovina, Julie K. Schwarz, Jin Zhang. An 18-gene expression model predicts resistance to standard of care therapy on 3-month follow up 18FDG-PET in locally advanced cervical cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3475.